Magnetic Resonance Imaging (MRI) can generate cross-sectional images in any plane (including oblique planes). Medical MRI most frequently relies on the relaxation properties of excited hydrogen nuclei (protons) in water and fat. When the object to be imaged is placed in a powerful, uniform magnetic field the spins of the atomic nuclei with non-integer spin numbers within the tissue all align either parallel to the magnetic field or anti-parallel. The output result of an MRI scan is an MRI contrast image or a series of MRI contrast images.
In order to understand MRI contrast, it is important to have some understanding of the time constants involved in relaxation processes that establish equilibrium following RF excitation. As the excited protons relax and realign, they emit energy at rates which are recorded to provide information about their environment. The realignment of proton spins with the magnetic field is termed longitudinal relaxation and the time (typically about 1 sec) required for a certain percentage of the tissue nuclei to realign is termed “Time 1” or T1. T2-weighted imaging relies upon local dephasing of spins following the application of the transverse energy pulse; the transverse relaxation time (typically <100 ms for tissue) is termed “Time 2” or T2. These relaxation times are also expressed as relaxation rates R1 (=1/T1) and R2 (=1/T2). The total signal depends on the number of protons, or proton density PD. On the scanner console all available parameters, such as echo time TE, repetition time TR, flip angle α and the application of preparation pulses (and many more), are set to certain values. Each specific set of parameters generates a particular signal intensity in the resulting images depending on the characteristics of the measured tissue.
In conventional contrast imaging the absolute signal intensity observed in the images has no direct meaning; it is rather the intensity difference, the contrast, between different tissues that lead to a diagnosis. A more quantitative approach can be applied based on the measurement of physical parameters such as R1, R2 and PD. These values are independent of scanner settings and hence reflect the underlying tissue.
A Bloch simulation model (see e.g. Levesque R, Pike G B. Characterizing healthy and diseased white matter using quantitative magnetization transfer and multicomponent T2 relaxometry: A unified view via a four-pool model. Mag Reson Med 2009; 62:1487-1496) can be set up to relate tissue composition to the expected observation of MR quantification results in a direct measurement of the included tissues, which could lead to MR computer aided diagnose.
One type of brain tissue of particular interest is called Myelin. Myelin is particularly interesting since it forms the insulating sheaths around the nerve axons in the brain. Degradation or damage to myelin may lead to a range of diseases such as dementia and multiple sclerosis. It can also be an important factor to determine the extent of edema, stroke or brain tumors. Myelin consists of thin layers of fatty tissue (semi-solids) and water.
There is a constant need to improve diagnostic and imaging methods relating to MRI. In particular methods and apparatuses for improved imaging and analysis of brain tissue such as myelin is desired.